: For over a century cardiovascular diseases have been the primary cause of death in the United States. Therefore, improved tools to aid in diagnosis and prognosis of atherosclerosis are needed. A step towards this goal is to evaluate the hypothesis that integrative multi-scale, multiphysics modeling is capable of predicting the growth and remodeling of atherogenesis in a simulated coronary artery. The methods required to accomplish this objective will involve 1) setting up a theoretical framework for a multiscale model capable of robustly integrating interactions from the protein to tissue level of a coronary artery, 2) establishing an accurate process to calculate the stresses resulting from pressurization and flow in this artery, 3) coupling these simulations to create a congruent multiscale model capable of simulating atherosclerotic plaque progression, and 4) validating model predictions to longitudinal in-vivo human and ex-vivo porcine data detailing plaque progression. Previously, we have shown that inclusive computational models are capable of predicting the hemodynamically, anatomically, and mechano-chemo-biologically varying aspects during arterial remodeling under healthy and hypertensive conditions. Since, this model was incapable of predicting the 3D changes, atherosclerotic plaques, and mechanical inhomogeneity present in the advanced stages of atherosclerosis, we present an approach combining agent based modeling (ABM) with finite element analysis (FEA) and computational fluid dynamics (CFD) to create a modeling tool that can predict the evolution of atherosclerotic plaque progression and instability. Together this model will be able to handle mechano-geometric complexity (FEA & CFD) and chemo- biological complexity (ABM) to a degree existing approaches cannot. From a basic science perspective, by integrating numerous cell-level behaviors one can better understand the underlying causes leading to plaque progression. Moreover, it will reveal areas that warrant further research or reveal emergent properties otherwise overlooked. Ultimately, a better multi-scale model of plaque evolution will be insightful for individualized decision making (e.g. to treat or not to treat a lesion) and foundational for design changes in interventional approaches (e.g. hypothesizing how an artery will respond to a pharmaceutical candidate, stent design or graft).